Population Status of White Sturgeon in the Lower Columbia River within Canada
Bibliographic record
Abstract
Abstract The subpopulation of white sturgeon Acipenser transmontanus in the Canadian portion of the Columbia River between Hugh L. Keenleyside Dam and the U.S.‐Canada border has been identified as endangered, with nearly 30 consecutive years of consistent recruitment failure. The objectives of this study were to determine the status and population attributes of this subpopulation. We estimated survival rates and abundance using catch‐curve analysis and mark‐recapture models. An annual survival rate of 89% (95% confidence interval [CI], 88‐90%) was estimated for the subpopulation using catch‐curve analysis for the time period 1993‐2004. The survival rates estimated from the mark‐recapture data were obtained using model‐averaged parameter estimates from a multistrata Cormack‐Jolly‐Seber model. The annual survival rate from the mark‐recapture model was estimated at 97% (95% CI, 92‐99%) from 1993 to 2004. The mark‐recapture methods estimated abundance for 2004 to be 1,157 individuals (95% CI, 414‐1,900). The mark‐recapture data suggest that the white sturgeon have low migration rates, ranging from 3% to 5% among sections of the river. Despite high estimated survival, high uncertainty as to the future viability of the white sturgeon subpopulation in this portion of the river remains, as natural recruitment is poor. The fish continue to age, and size and age‐frequency data suggest that recruitment failure continues in this subpopulation with minimal presence of wild juvenile or subadult white sturgeon detected.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".